AI Article Synopsis
- Perception, learning, and high-level cognition depend on identifying patterns in data, but there are countless patterns that could fit any given set of data.
- The cognitive system tends to select patterns that are considered 'sensible' based on simplicity, as suggested by various fields including epistemology, philosophy, and computational theories.
- The article discusses research that supports the idea that simplicity influences cognitive processes, highlighting relevant mathematical theories, computational findings, and empirical evidence.
Article Abstract
Much of perception, learning and high-level cognition involves finding patterns in data. But there are always infinitely many patterns compatible with any finite amount of data. How does the cognitive system choose 'sensible' patterns? A long tradition in epistemology, philosophy of science, and mathematical and computational theories of learning argues that patterns 'should' be chosen according to how simply they explain the data. This article reviews research exploring the idea that simplicity drives a wide range of cognitive processes. We outline mathematical theory, computational results and empirical data that underpin this viewpoint.
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| http://dx.doi.org/10.1016/s1364-6613(02)00005-0 | DOI Listing |
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